Stock Analysis Pro Framework

What problem it solves

Single-stock analysis often turns into disconnected claims: price action, financial statements, and news snippets are judged separately, leaving no auditable evidence chain or consistent risk vocabulary. This skill turns a stock or company request into a structured institutional-style research process, so the output moves from “leans bullish” to documented multi-module reasoning.

How it works

It uses a fixed 10-module framework: macro, trend, company competency, valuation, earnings and analyst forecasts, competitor benchmarking, risk, ESG and governance, catalysts, and investment summary. Each module answers one core question and is rated 1-5; risk is scored inversely, where 5 means lower risk. The overall score averages the nine non-summary modules and maps to stances such as Strong Buy, Buy, Hold, Reduce, and Avoid.

Key steps include:
- Data first: prioritize SEC filings, investor relations pages, consensus platforms, aggregators, and macro sources before relying on headlines.
- Balanced cases: write bull and bear cases in each module, and mark missing or estimated data with ⚠️.
- Traceable scoring: justify signals such as WACC, terminal growth rate, RSI, and MACD, instead of treating indicators as standalone buy/sell triggers.

Boundaries

This is best used as an analytical template and research checklist, not as a live market feed or automatic trading signal. Its quality depends on source availability. If TTM metrics, EV/Sales, ESG ratings, or event dates are missing, the conclusion should be downgraded to “needs more data.” For short-term theses, weight trend and catalysts more heavily; for long-term theses, weight macro, company competency, valuation, and ESG more heavily.